E-LIB Suche - Ergebnisse für: Vapnik, Vladimir

1

Reinforced SVM method and memorization mechanisms:

Vapnik, Vladimir ; Izmailov, Rauf
Pattern Recognition. 119 (2021) - p. 108018 , 2021

Link: https://doi.org/10.1016/..

2

Rethinking statistical learning theory: learning using stat..:

Vapnik, Vladimir ; Izmailov, Rauf
Machine Learning. 108 (2018) 3 - p. 381-423 , 2018

Link: https://doi.org/10.1007/..

3

Knowledge transfer in SVM and neural networks:

Vapnik, Vladimir ; Izmailov, Rauf
Annals of Mathematics and Artificial Intelligence. 81 (2017) 1-2 - p. 3-19 , 2017

Link: https://doi.org/10.1007/..

4

Constructive setting for problems of density ratio estimati..:

Vapnik, Vladimir ; Braga, Igor ; Izmailov, Rauf
Statistical Analysis and Data Mining: The ASA Data Science Journal. 8 (2015) 3 - p. 137-146 , 2015

Link: https://doi.org/10.1002/..

5

Machine learning classification with confidence: Applicatio..:

Nouretdinov, Ilia ; Costafreda, Sergi G. ; Gammerman, Alexander...
NeuroImage. 56 (2011) 2 - p. 809-813 , 2011

Link: https://doi.org/10.1016/..

6

Falsificationism and Statistical Learning Theory: Comparing..:

Corfield, David ; Schölkopf, Bernhard ; Vapnik, Vladimir
Journal for General Philosophy of Science / Zeitschrift für allgemeine Wissenschaftstheorie. 40 (2009) 1 - p. 51-58 , 2009

Link: https://www.jstor.org/st..

7

Falsificationism and Statistical Learning Theory: Comparing..:

Corfield, David ; Schölkopf, Bernhard ; Vapnik, Vladimir
Journal for General Philosophy of Science. 40 (2009) 1 - p. 51-58 , 2009

Link: https://doi.org/10.1007/..

8

A new learning paradigm: Learning using privileged informat..:

Vapnik, Vladimir ; Vashist, Akshay
Neural Networks. 22 (2009) 5-6 - p. 544-557 , 2009

Link: https://doi.org/10.1016/..

9

Large margin vs. large volume in transductive learning:

El-Yaniv, Ran ; Pechyony, Dmitry ; Vapnik, Vladimir
Machine Learning. 72 (2008) 3 - p. 173-188 , 2008

Link: https://doi.org/10.1007/..

10

Inference with the Universum:

, In: Proceedings of the 23rd international conference on Machine learning,

Weston, Jason ; Collobert, Ronan ; Sinz, Fabian.. - p. 1009-1016 , 2006

Link: https://dl.acm.org/doi/1..

11

Support-vector networks:

Cortes, Corinna ; Vapnik, Vladimir
Machine Learning. 20 (1995) 3 - p. 273-297 , 1995

Link: https://doi.org/10.1007/..

12

A training algorithm for optimal margin classifiers:

, In: Proceedings of the fifth annual workshop on Computational learning theory,

Boser, Bernhard E. ; Guyon, Isabelle M. ; Vapnik, Vladimir N. - p. 144-152 , 1992

Link: https://dl.acm.org/doi/1..

13

Unifying distillation and privileged information:

Lopez-Paz, David ; Bottou, Léon ; Schölkopf, Bernhard.
http://arxiv.org/abs/1511.03643. , 2015

Link: http://arxiv.org/abs/151..

14

Constructive Setting of the Density Ratio Estimation Proble..:

Vapnik, Vladimir ; Braga, Igor ; Izmailov, Rauf
http://arxiv.org/abs/1306.0407. , 2013

Link: http://arxiv.org/abs/130..

15

Learning by Transduction:

Gammerman, Alex ; Vovk, Volodya ; Vapnik, Vladimir
http://arxiv.org/abs/1301.7375. , 2013

Link: http://arxiv.org/abs/130..